Ns126:Calendar/NOTES/2016-2-24

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Layer specific MHBs with hyper or hypo-MHL[edit]

motivation[edit]

  • group tissues of same gem layer
  • identify layder specific MHBs with hyper/hypo MHL

Layer specific hyper-MHL regions[edit]

  • In total we identified 114 ectoderm-specific MHBs (99 hyper- and 15 hypo-methylated), 75 endoderm specific MHBs (58 hyper and 17 hypo-methylated) and 31 mesoderm specific MHBs (9 hyper and 22 hypo-methylated) (see Methods, Supplementary Table 3).
  • Figure saved in laptop: C:\Users\shicheng\Dropbox\Project\methylation\monod\analysis\layer_specfic_mhl
  • Raw data saved in Genome-miner: /home/shg047/monod/dec
Rbedtools<-function(functionstring="intersectBed",bed1,bed2,opt.string=""){
#create temp files
a.file=tempfile()
b.file=tempfile()
out =tempfile()
options(scipen =99) # not to use scientific notation when writing out
#write bed formatted dataframes to tempfile
write.table(bed1,file=a.file,quote=F,sep="\t",col.names=F,row.names=F)
write.table(bed2,file=b.file,quote=F,sep="\t",col.names=F,row.names=F)
# create the command string and call the command using system()
command=paste(functionstring,"-a",a.file,"-b",b.file,opt.string,">",out,sep=" ")
cat(command,"\n")
try(system(command))
res=read.table(out,header=F)
unlink(a.file);unlink(b.file);unlink(out)
return(res)
}
cor2bed<-function(cor){
a<-unlist(lapply(strsplit(as.character(cor),split=c(":")),function(x) strsplit(x,"-")))
bed<-matrix(a,ncol=3,byrow=T)
return(data.frame(bed))
}
setwd("C:\\Users\\shicheng\\Dropbox\\Project\\methylation\\monod\\analysis\\layer_specfic_mhl")
/home/shg047/monod/dec/Table.GSI.layer.mhl.WGBS.Remove.H1.WBC.rlt.txt
data=read.table("/home/shg047/monod/dec/Table.GSI.layer.mhl.WGBS.Remove.H1.WBC.rlt.txt",head=T,sep="\t",as.is=T)
head(data)
newdata=subset(data,GSI>0.6)
table(subset[,2])
mesoderm<-subset(newdata,group=="Mesoderm")
ectoderm<-subset(newdata,group=="Ectoderm")
endoderm<-subset(newdata,group=="Endoderm")
mesodermBed<-cor2bed(mesoderm[,1])
ectodermBed<-cor2bed(ectoderm[,1])
endodermBed<-cor2bed(endoderm[,1])
# change to laptop to plot histgram
setwd("C:\\Users\\shicheng\\Dropbox\\Project\\methylation\\monod\\analysis\\layer_specfic_mhl")
data=read.table("Table.GSI.layer.mhl.WGBS.Remove.H1.WBC.rlt.txt",head=T,sep="\t",as.is=T)
pdf("hist.layer.specfic.pdf")
hist(data[,3],breaks=30,col="green",ylim=c(0,4000),xlab="Layer Specfic Index",main="")
dev.off()
Rbedtools(functionstring="intersectBed",bed1=mesodermBed,bed2=ectodermBed,opt.string="-wa -u")
table<-c(99,66,9)
names(table)<-c("Ectoderm","Endoderm","Mesoderm")
barplot(table,ylim=c(0,100),col="green")
  • Layer specific MHBs with hyper-MHL
Ectoderm Endoderm Mesoderm
99       66        9


region group GSI
chr8:29387092-29387216 Ectoderm 0.659537333117352
chr19:39898750-39898769 Ectoderm 0.622260349526761
chr11:120095770-120095841 Ectoderm 0.638436015070805
chr8:143298766-143298852 Ectoderm 0.629089907645855
chr16:21657412-21657574 Ectoderm 0.6376721097517
chr5:92934330-92934406 Ectoderm 0.667334656563231
chr3:43811289-43811331 Ectoderm 0.658785740481031
chr17:8601976-8601988 Ectoderm 0.602106513421994
chr10:121030613-121030661 Ectoderm 0.620355461223933
chr1:193377965-193378092 Ectoderm 0.612384341440121
chr18:13138062-13138194 Ectoderm 0.630293124544825
chr11:128065158-128065181 Ectoderm 0.615776035999425
chr7:115995198-115995218 Ectoderm 0.639634173881391
chr2:3583886-3583967 Ectoderm 0.629371815688128
chr21:24503682-24503775 Ectoderm 0.60393446974352
chr8:42750431-42750654 Ectoderm 0.609058674400317
chr1:22259946-22260017 Ectoderm 0.600124624290291
chr5:106878574-106878620 Ectoderm 0.609389311058491
chr10:123496262-123496391 Ectoderm 0.633479349721013
chr9:97713223-97713340 Ectoderm 0.602639172712739
chr6:43670518-43670599 Ectoderm 0.616096733986403
chr11:36706919-36707044 Ectoderm 0.639962708993761
chr15:42187197-42187218 Ectoderm 0.607623926207222
chr2:65804207-65804281 Ectoderm 0.603236104868574
chr17:77766959-77766979 Ectoderm 0.66624153932879
chr1:159893108-159893168 Ectoderm 0.671409324490059
chr2:121495455-121495544 Ectoderm 0.616705504439262
chr8:19522859-19522941 Ectoderm 0.61492324445635
chr19:38886666-38886702 Ectoderm 0.670488181288092
chr1:41849182-41849197 Ectoderm 0.601497796230824
chr19:38886138-38886153 Ectoderm 0.60215755360785
chr11:110065132-110065260 Ectoderm 0.620350268299807
chr18:28827952-28828043 Ectoderm 0.62733392232416
chr2:110438251-110438428 Ectoderm 0.609815651189271
chr11:74854298-74854413 Ectoderm 0.604758661736277
chr20:43966567-43966613 Ectoderm 0.633100005220329
chr2:85811833-85811846 Ectoderm 0.603742595694347
chr7:101961892-101961907 Ectoderm 0.636479562937856
chr22:19710901-19710936 Ectoderm 0.643860942397404
chr17:76732402-76732485 Ectoderm 0.630309428917436
chr16:88837350-88837417 Ectoderm 0.639956789529288
chr20:49262297-49262329 Ectoderm 0.62648816520905
chr1:186181479-186181655 Ectoderm 0.605638208915313
chr8:134203271-134203327 Ectoderm 0.620493153208632
chr5:169894194-169894243 Ectoderm 0.633726208035661
chr5:150403465-150403482 Ectoderm 0.62441239036749
chr9:137220495-137220592 Ectoderm 0.600899351123174
chr2:74209501-74209580 Ectoderm 0.602032376155113
chr20:5059205-5059233 Ectoderm 0.612938330332136
chr1:227545247-227545308 Ectoderm 0.609135849889118
chr7:33080614-33080718 Ectoderm 0.639600512160286
chr1:59362446-59362543 Ectoderm 0.619376367184664
chr2:203037243-203037337 Ectoderm 0.625115647207567
chr17:77767155-77767186 Ectoderm 0.638533123496661
chr7:43214618-43214840 Ectoderm 0.600723642889573
chr2:71644560-71644595 Ectoderm 0.641067698816342
chr7:139529310-139529349 Ectoderm 0.6134098285564
chr1:196946446-196946570 Ectoderm 0.610806427586173
chr2:42277283-42277335 Ectoderm 0.628058759527649
chr11:123016107-123016154 Ectoderm 0.657923031208003
chr1:229978819-229978864 Ectoderm 0.623894630744394
chr17:57078908-57079003 Ectoderm 0.610926283216838
chr7:22617356-22617407 Ectoderm 0.667929987625616
chr7:2757237-2757316 Ectoderm 0.601252252195626
chr3:36949925-36949965 Ectoderm 0.662948818910667
chr1:59361425-59361492 Ectoderm 0.658198739198946
chr21:40138947-40139045 Ectoderm 0.641545688027849
chr22:33018091-33018133 Ectoderm 0.605395609371496
chr10:45916330-45916353 Ectoderm 0.627360449725662
chr6:154975205-154975246 Ectoderm 0.607656376219889
chr21:34659414-34659513 Ectoderm 0.614947673577016
chr12:113065670-113065803 Ectoderm 0.637109038086428
chr11:61456495-61456567 Ectoderm 0.603736020447996
chr1:204592540-204592575 Ectoderm 0.600751451839705
chr22:38614662-38614758 Ectoderm 0.65680933946711
chr17:76588327-76588445 Ectoderm 0.655514821551318
chr16:86417535-86417723 Ectoderm 0.621362797865302
chr6:159128335-159128360 Ectoderm 0.648877652085264
chr3:167073066-167073152 Ectoderm 0.648045424921539
chr3:186928712-186928778 Ectoderm 0.610146996868578
chr11:57089649-57089743 Ectoderm 0.62677395784954
chr6:111239079-111239184 Ectoderm 0.63037773416189
chr17:48764127-48764188 Ectoderm 0.60627221893251
chr6:168197479-168197510 Ectoderm 0.632032999449708
chr15:74671324-74671459 Ectoderm 0.623154091775709
chr19:58868085-58868120 Ectoderm 0.674814055759394
chr4:153878727-153878844 Ectoderm 0.62419394200263
chr3:172280812-172280854 Ectoderm 0.625528145281659
chr3:122640840-122640863 Ectoderm 0.606059008480575
chr1:8064972-8064983 Ectoderm 0.644939000855723
chr12:248974-249014 Ectoderm 0.657233142275506
chr19:16272368-16272434 Ectoderm 0.610474524921455
chr5:132444216-132444275 Ectoderm 0.602807461907881
chr15:31890779-31891030 Ectoderm 0.603133103058883
chr21:45579708-45579771 Ectoderm 0.612035579928314
chr22:24906975-24907189 Ectoderm 0.604317977687824
chr21:45304017-45304067 Ectoderm 0.615161807537595
chr17:76732735-76732773 Ectoderm 0.627406271009881
chr20:21250244-21250339 Ectoderm 0.607049177788986
chr17:2119276-2119367 Endoderm 0.621555865969221
chr1:1957051-1957084 Endoderm 0.602650908155007
chr9:35689643-35689690 Endoderm 0.619387701280056
chr2:47241811-47241842 Endoderm 0.662829312044627
chr5:172305920-172305935 Endoderm 0.670739265276362
chr14:38080580-38080592 Endoderm 0.639966474713107
chr1:230476437-230476574 Endoderm 0.635030322574557
chr10:104575592-104575618 Endoderm 0.609149408140753
chr8:12957933-12957984 Endoderm 0.643490818086236
chr5:151043109-151043181 Endoderm 0.680177807411657
chr4:7632491-7632709 Endoderm 0.652423230457514
chr19:3670199-3670225 Endoderm 0.634998241133357
chr7:114584954-114585002 Endoderm 0.603616478692203
chr1:234669276-234669303 Endoderm 0.616809574818785
chr16:22229894-22229955 Endoderm 0.607629291159365
chr10:6216405-6216443 Endoderm 0.602971624717696
chr9:124615379-124615452 Endoderm 0.633955823125635
chr2:37875819-37875959 Endoderm 0.602628500656313
chr2:64242660-64242800 Endoderm 0.60726399310844
chr2:242101288-242101347 Endoderm 0.608076333824482
chr16:1560025-1560087 Endoderm 0.651972214196267
chr11:118081886-118081999 Endoderm 0.6029309710898
chr6:157372211-157372306 Endoderm 0.634278618167255
chr11:65683490-65683558 Endoderm 0.636307514242888
chr18:46316989-46317041 Endoderm 0.624166723941027
chr16:10832062-10832121 Endoderm 0.611440520083738
chr8:1811724-1811734 Endoderm 0.604615438333278
chr22:44759564-44759570 Endoderm 0.610192616512951
chr11:107906691-107906721 Endoderm 0.605751844696818
chr2:239358562-239358706 Endoderm 0.614617410007429
chr1:25062843-25062863 Endoderm 0.670823332436485
chr4:37624974-37625026 Endoderm 0.6544427274209
chr19:36642990-36643069 Endoderm 0.656605450961024
chr12:6664139-6664180 Endoderm 0.669123041535702
chr11:44161686-44161822 Endoderm 0.628887015251611
chr7:459050-459072 Endoderm 0.60012029687524
chr19:39154668-39154690 Endoderm 0.663027710309978
chr17:66511557-66511576 Endoderm 0.631028220970854
chr11:47629283-47629316 Endoderm 0.634080728472571
chr22:34271616-34271645 Endoderm 0.615941002445972
chr1:225954691-225954718 Endoderm 0.601078618642703
chr11:46732432-46732450 Endoderm 0.632603084148886
chr4:151504919-151504983 Endoderm 0.621077562503555
chr11:24086083-24086150 Endoderm 0.608691231029366
chr22:18335966-18336049 Endoderm 0.670754545443272
chr19:18761285-18761327 Endoderm 0.68028737010478
chr5:54887639-54887649 Endoderm 0.652970324942108
chr9:93682361-93682514 Endoderm 0.665920831412597
chr3:170893533-170893551 Endoderm 0.603621933335352
chr3:171024840-171024914 Endoderm 0.636779220273703
chr14:59894932-59895017 Endoderm 0.61228529088177
chr2:1656976-1657034 Endoderm 0.618587759655055
chr16:69961433-69961448 Endoderm 0.631835214629571
chr14:102394447-102394465 Endoderm 0.612365707941321
chr7:6202081-6202133 Endoderm 0.611591150947358
chr19:38664210-38664243 Endoderm 0.602726833114876
chr1:10292194-10292416 Endoderm 0.653640769186138
chr20:19357121-19357136 Endoderm 0.654714700397522
chr2:204553596-204553702 Endoderm 0.601402898925884
chr6:157469645-157469672 Endoderm 0.6380499171651
chr10:115386647-115386737 Endoderm 0.622056663225908
chr2:240234683-240234705 Endoderm 0.612158498128861
chr19:15514987-15514998 Endoderm 0.601666018050405
chr2:109196275-109196451 Endoderm 0.634236535885808
chr12:109240568-109240631 Endoderm 0.614972599326848
chr13:42188452-42188507 Endoderm 0.604875957545443
chr16:85394306-85394334 Mesoderm 0.603027122263449
chr14:34493536-34493559 Mesoderm 0.661457016899424
chr17:79322621-79322654 Mesoderm 0.609437589321225
chr11:655465-655517 Mesoderm 0.638631266023567
chr9:4664295-4664543 Mesoderm 0.622455538468081
chr11:117684083-117684169 Mesoderm 0.614193089173044
chr17:80847496-80847545 Mesoderm 0.614992470215796
chr5:158879531-158879581 Mesoderm 0.631390177181746
chr11:34847402-34847459 Mesoderm 0.657593838020926

Layer specific hypo-MHL regions (LSMHB)[edit]

  • code in Genome-miner
library("impute")
RawNARemove<-function(data,missratio=0.3){
threshold<-(missratio)*dim(data)[2]
NaRaw<-which(apply(data,1,function(x) sum(is.na(x))>threshold))
zero<-which(apply(data,1,function(x) all(x==0))==T)
NaRAW<-c(NaRaw,zero)
if(length(NaRAW)>0){
dat<-data[-NaRAW,]
}else{
dat<-data;
}
dat
}
###################################################################################################################
setwd("/home/shg047/monod/dec")
infile="WGBS_methHap_load_matrix_20Oct2015.txt";
file1<-read.table(infile,head=T,sep="\t",row.names=1,as.is=T,check.names=F)
# miss value detection and imputation
library("impute")
f2<-RawNARemove(file1,missratio=0.3)
f2<-impute.knn(data.matrix(f2))$data
colnames(f2)
library("preprocessCore")
f2.t1<-normalize.quantiles(f2[,13:58])
library("sva")
batch=c(rep(1,10),rep(2,36))
f2.t2<-ComBat(f2.t1, batch, mod=NULL, par.prior = TRUE,prior.plots = FALSE)
f2[,13:58]<-f2.t2
# re-assign colnames
colnames(f2)
colnames(f2)<-gsub("_","-",colnames(f2))
colname2<-unlist(lapply(colnames(f2),function(x) unlist(strsplit(x,"[.]"))[1]))
colname2
colnames(f2)<-colname2
# be sure all the sample information has been stored in the following database
saminfo2<-read.table("/home/shg047/monod/phase2/newsaminfo.txt",head=T,sep="\t",as.is=T)
saminfo2<-saminfo2[match(colname2,saminfo2[,1]),]
saminfo2
colnames(f2)<-saminfo2[,2]
saminfo3<-read.table("/home/shg047/monod/saminfo/tissue2Layer.txt",head=T,sep="\t",as.is=T)
f2<-f2[,saminfo2[,2] %in% saminfo3[,1]]
fn<-f2
colnames(fn)<-saminfo3[match(colnames(fn),saminfo3[,1]),2]
group=names(table(colnames(fn)))
index=colnames(fn)
gsi<-c()
gmaxgroup<-c()
pvalue=apply(fn,1,function(x) summary(aov(x~index))1[["Pr(>F)"]][1])   # R list will not be correctly shown in wiki, you can see raw script in edit mode
pvalue=apply(fn,1,function(x) summary(aov(x~index))15[1])          # R list will not be correctly shown in wiki, you can see raw script in edit mode
SigDiffMHBANOVA<-fn[match(names(which(pvalue<9.223561e-07)),rownames(fn)),]
save(SigDiffMHBANOVA,file="SigDiffMHBANOVA.RData")
setwd("C:\\Users\\shicheng\\Dropbox\\Project\\methylation\\monod\\analysis\\layer_specfic_mhl\\anova")
library("gplots")
load("SigDiffMHBANOVA.RData")
SigDiffMHBANOVA[SigDiffMHBANOVA<0]<-0
SigDiffMHBANOVA[SigDiffMHBANOVA>1]<-1
SigDiffMHBANOVA<-SigDiffMHBANOVA[,order(colnames(SigDiffMHBANOVA))]
pdf("Figure.supervised.layer.mhl.single.cpg.heatmap.analysis.combat.quantile.pdf")
col=colorRampPalette(c("yellow", "blue"))(20)
rlt<-heatmap.2(data.matrix(SigDiffMHBANOVA),col=col,trace="none",density.info="none",Colv=T,Rowv=T,key=T,keysize=1,cexCol=0.65,cexRow=0.15)
dev.off()
  • Layer specific MHBs with hypo-MHL
# Endoderm specific MHB with hypo-MHL
chr11:16023703−16023847
chr8:131774761−131774884
chr7:100540088−100540103
chr5:10746894−10747078
chr14:69095543−69095569
chr1:120333406−120333474
chr4:185071507−185071556
chr15:63682373−63682439
chr6:136869788−136869917
chr15:69854565−69854745
chr2:235372763−235372775
chr7:150074899−150075088
chr11:86716322−86716463
chr10:125866028−125866205
chr20:51697944−51698112
chr11:45670341−45670390
chr13:107772692−107772845
# Mesoderm specific MHB with hypo-MHL
chr2:227555394−227555409
chr14:38091850−38091925
chr14:38080503−38080551
chr7:99984750−99984849
chr4:55650506−55650562
chr10:13726663−13726680
chr2:204553596−204553702
chr14:38080580−38080592
chr9:137296113−137296129
chr12:6664139−6664180
chr5:151043109−151043181
chr19:39154699−39154740
chr6:157469645−157469672
chr19:36642990−36643069
chr11:68695417−68695433
chr19:39154668−39154690
chr3:114343145−114343262
chr2:109196275−109196451
chr8:61764645−61764654
chr4:140737662−140737678
chr7:116409578−116409798
chr2:30574091−30574117
# Ectoderm specific MHB with hypo-MHL
chr20:32010750−32010885
chr4:56238469−56238664
chr12:15759107−15759119
chr2:27268131−27268232
chr15:43812034−43812191
chr2:118688440−118688576
chr7:141359663−141359879
chr8:9954912−9955067
chr9:92683370−92683559
chr2:201964657−201964684
chr1:93623462−93623507
chr3:142199628−142199667
chr5:118285675−118285700
chr8:95745542−95745573
chr6:107096030−107096062
  • TFBS
for i in `ls /home/shg047/db/hg19/encode/encode.*.hg19.bed`
do
bedtools window -w 100 -a endo.mhb.hypo.bed -b $i >> endo.mhb.hypo.tf
bedtools window -w 100 -a meso.mhb.hypo.bed -b $i >> meso.mhb.hypo.tf
bedtools window -w 100 -a ecto.mhb.hypo.bed -b $i >> ecto.mhb.hypo.tf
done
cat endo.mhb.hypo.tf | awk '{print $4}' | sort -u > endo.mhb.hypo.uni.tf
cat meso.mhb.hypo.tf | awk '{print $4}' | sort -u > meso.mhb.hypo.uni.tf
cat ecto.mhb.hypo.tf | awk '{print $4}' | sort -u > ecto.mhb.hypo.uni.tf
  • File Address in Genome-miner
/home/shg047/monod/layer/endo.mhb.hypo.bed
/home/shg047/monod/layer/meso.mhb.hypo.bed
/home/shg047/monod/layer/ecto.mhb.hypo.bed
  • Venn graph


  • Gene Ontolgoy
  • Endoderm
Category Term Count  % PValue Fold Enrichment FDR
GOTERM_MF_FAT GO:0003700~transcription factor activity 26 86.66666667 1.02E-24 11.54044444 1.08E-21
SP_PIR_KEYWORDS dna-binding 27 90 1.08E-23 9.267398287 1.06E-20
SP_PIR_KEYWORDS transcription regulation 27 90 8.77E-23 8.544669299 8.59E-20
SP_PIR_KEYWORDS Transcription 27 90 1.55E-22 8.359005311 1.51E-19
GOTERM_MF_FAT GO:0030528~transcription regulator activity 27 90 1.10E-21 7.72797619 1.16E-18
GOTERM_MF_FAT GO:0003677~DNA binding 29 96.66666667 2.73E-20 5.384055484 2.88E-17
SP_PIR_KEYWORDS nucleus 30 100 1.12E-19 4.491010974 1.10E-16
GOTERM_BP_FAT GO:0006350~transcription 27 90 1.82E-18 5.794954783 2.67E-15
GOTERM_BP_FAT GO:0045449~regulation of transcription 28 93.33333333 1.10E-17 4.854338075 1.62E-14
GOTERM_MF_FAT GO:0043565~sequence-specific DNA binding 18 60 5.83E-16 12.83327842 5.88E-13
GOTERM_BP_FAT GO:0006355~regulation of transcription, DNA-dependent 24 80 9.18E-16 6.104004512 1.31E-12
GOTERM_BP_FAT GO:0051252~regulation of RNA metabolic process 24 80 1.62E-15 5.969332598 2.45E-12
SP_PIR_KEYWORDS activator 13 43.33333333 4.59E-12 16.02916667 4.50E-09
SP_PIR_KEYWORDS DNA binding 11 36.66666667 3.88E-11 20.74362745 3.80E-08
GOTERM_BP_FAT GO:0006357~regulation of transcription from RNA polymerase II promoter 14 46.66666667 8.55E-10 8.683723063 1.26E-06
GOTERM_CC_FAT GO:0031981~nuclear lumen 13 43.33333333 5.12E-09 6.741014199 5.27E-06
GOTERM_BP_FAT GO:0010628~positive regulation of gene expression 12 40 1.43E-08 9.313597246 2.10E-05
GOTERM_MF_FAT GO:0003702~RNA polymerase II transcription factor activity 9 30 4.24E-08 15.96270492 4.47E-05
GOTERM_CC_FAT GO:0070013~intracellular organelle lumen 13 43.33333333 5.40E-08 5.494362332 5.55E-05
GOTERM_CC_FAT GO:0043233~organelle lumen 13 43.33333333 7.00E-08 5.370588235 7.20E-05
GOTERM_MF_FAT GO:0008134~transcription factor binding 11 36.66666667 8.65E-08 9.279597141 9.12E-05
GOTERM_CC_FAT GO:0031974~membrane-enclosed lumen 13 43.33333333 8.76E-08 5.266417343 9.01E-05
GOTERM_BP_FAT GO:0045941~positive regulation of transcription 11 36.66666667 1.43E-07 8.794799054 2.11E-04
GOTERM_BP_FAT GO:0045935~positive regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process 11 36.66666667 3.67E-07 7.949145299 5.39E-04
GOTERM_BP_FAT GO:0045893~positive regulation of transcription, DNA-dependent 10 33.33333333 4.17E-07 9.453529001 6.13E-04
GOTERM_BP_FAT GO:0051254~positive regulation of RNA metabolic process 10 33.33333333 4.47E-07 9.374913375 6.58E-04
GOTERM_BP_FAT GO:0051173~positive regulation of nitrogen compound metabolic process 11 36.66666667 4.91E-07 7.702277433 7.21E-04
GOTERM_BP_FAT GO:0010557~positive regulation of macromolecule biosynthetic process 11 36.66666667 5.65E-07 7.584505607 8.31E-04
GOTERM_BP_FAT GO:0010604~positive regulation of macromolecule metabolic process 12 40 7.44E-07 6.31411902 0.001094283
GOTERM_BP_FAT GO:0045944~positive regulation of transcription from RNA polymerase II promoter 9 30 7.69E-07 10.93908356 0.001130801
GOTERM_BP_FAT GO:0031328~positive regulation of cellular biosynthetic process 11 36.66666667 8.65E-07 7.241265207 0.001271592
GOTERM_BP_FAT GO:0009891~positive regulation of biosynthetic process 11 36.66666667 9.87E-07 7.137074341 0.001451883
GOTERM_BP_FAT GO:0010551~regulation of specific transcription from RNA polymerase II promoter 6 20 1.51E-06 28.78297872 0.002226717
GOTERM_MF_FAT GO:0046983~protein dimerization activity 10 33.33333333 1.71E-06 7.984624846 0.001801204
INTERPRO IPR004827:Basic-leucine zipper (bZIP) transcription factor 5 16.66666667 2.04E-06 52.38679245 0.002102847
GOTERM_MF_FAT GO:0016563~transcription activator activity 9 30 2.21E-06 9.499756098 0.002335511
UP_SEQ_FEATURE DNA-binding region:Basic motif 6 20 4.02E-06 23.74285714 0.004570435
SMART SM00338:BRLZ 5 16.66666667 8.44E-06 35.68789308 0.006326719
GOTERM_BP_FAT GO:0032583~regulation of gene-specific transcription 6 20 8.68E-06 20.19104478 0.0127626
UP_SEQ_FEATURE domain:Leucine-zipper 5 16.66666667 2.21E-05 28.95909091 0.025103574
GOTERM_BP_FAT GO:0006351~transcription, DNA-dependent 7 23.33333333 3.00E-05 10.81004566 0.044147909
GOTERM_BP_FAT GO:0032774~RNA biosynthetic process 7 23.33333333 3.24E-05 10.66396396 0.047654411
SP_PIR_KEYWORDS repressor 7 23.33333333 3.95E-05 10.31762452 0.038665521
UP_SEQ_FEATURE zinc finger region:NR C4-type 4 13.33333333 4.27E-05 56.63111111 0.048544142
UP_SEQ_FEATURE DNA-binding region:Nuclear receptor 4 13.33333333 4.27E-05 56.63111111 0.048544142
  • Mesoderm
Category Term Count  % PValue Fold Enrichment FDR
SP_PIR_KEYWORDS transcription regulation 12 92.30769231 1.87E-10 8.763763384 1.64E-07
SP_PIR_KEYWORDS Transcription 12 92.30769231 2.38E-10 8.573338781 2.08E-07
GOTERM_BP_FAT GO:0045449~regulation of transcription 12 92.30769231 1.30E-08 5.201076509 1.72E-05
SP_PIR_KEYWORDS nucleus 13 100 1.47E-08 4.491010974 1.28E-05
GOTERM_MF_FAT GO:0016564~transcription repressor activity 7 53.84615385 8.27E-08 23.96650844 8.10E-05
GOTERM_MF_FAT GO:0030528~transcription regulator activity 10 76.92307692 1.70E-07 7.15553351 1.67E-04
GOTERM_BP_FAT GO:0016481~negative regulation of transcription 7 53.84615385 5.90E-07 17.19244735 7.77E-04
GOTERM_BP_FAT GO:0010629~negative regulation of gene expression 7 53.84615385 1.02E-06 15.65740741 0.001345482
GOTERM_BP_FAT GO:0045934~negative regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process 7 53.84615385 1.12E-06 15.41276042 0.001475649
GOTERM_BP_FAT GO:0051172~negative regulation of nitrogen compound metabolic process 7 53.84615385 1.21E-06 15.20488118 0.001597891
GOTERM_MF_FAT GO:0008134~transcription factor binding 7 53.84615385 1.44E-06 14.76299545 0.001412732
GOTERM_BP_FAT GO:0010558~negative regulation of macromolecule biosynthetic process 7 53.84615385 1.65E-06 14.42656917 0.002173387
GOTERM_BP_FAT GO:0031327~negative regulation of cellular biosynthetic process 7 53.84615385 1.92E-06 14.06654783 0.002519407
GOTERM_BP_FAT GO:0006350~transcription 10 76.92307692 2.11E-06 5.365698874 0.002778119
GOTERM_BP_FAT GO:0009890~negative regulation of biosynthetic process 7 53.84615385 2.17E-06 13.77196044 0.002850924
GOTERM_CC_FAT GO:0005654~nucleoplasm 7 53.84615385 2.64E-06 11.27160494 0.002668839
SP_PIR_KEYWORDS repressor 6 46.15384615 4.02E-06 20.40848806 0.003505542
GOTERM_CC_FAT GO:0044451~nucleoplasm part 6 46.15384615 7.61E-06 15.35375375 0.007709187
GOTERM_BP_FAT GO:0010605~negative regulation of macromolecule metabolic process 7 53.84615385 9.13E-06 10.75113533 0.012014286
GOTERM_BP_FAT GO:0006355~regulation of transcription, DNA-dependent 9 69.23076923 9.79E-06 5.72250423 0.012881602
GOTERM_BP_FAT GO:0051252~regulation of RNA metabolic process 9 69.23076923 1.16E-05 5.596249311 0.015267288
UP_SEQ_FEATURE domain:Leucine-zipper 4 30.76923077 3.93E-05 53.46293706 0.04077532
SP_PIR_KEYWORDS dna-binding 8 61.53846154 4.11E-05 6.336682589 0.035859411
GOTERM_CC_FAT GO:0031981~nuclear lumen 7 53.84615385 4.82E-05 6.856245211 0.04883162